Autoregressive state spatial modeling of soil bulk density and organic carbon in fields under different tillage system

Uncontrolled transit operations could be responsible of repetitive patterns of soil properties. Cyclic spatial structure patterns of soil bulk density (BD), soil organic carbon [OC] and water content [WC] in farm fields were assessed with spectra and cross spectra analysis in a 100 m-long transect s...

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Detalles Bibliográficos
Otros Autores: Rienzi, Eduardo Abel, Maggi, Alejandro Esteban, Scroffa, Marcos, López, Valeria Carolina, Cabanella, P.
Formato: Artículo
Lenguaje:Inglés
Materias:
UNCONTROLLED TRAFFIC
SOIL BULK DENSITY
SOIL ORGANIC CARBON
WATER CONTENT
COSPECTRA ANALYSIS
Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2016rienzi.pdf
LINK AL EDITOR
Aporte de:Registro referencial: Solicitar el recurso aquí
Biblioteca Central (FAUBA) de Universidad de Buenos Aires
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024 |a 10.1016/j.still.2016.01.006 
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245 1 0 |a Autoregressive state spatial modeling of soil bulk density and organic carbon in fields under different tillage system 
520 |a Uncontrolled transit operations could be responsible of repetitive patterns of soil properties. Cyclic spatial structure patterns of soil bulk density (BD), soil organic carbon [OC] and water content [WC] in farm fields were assessed with spectra and cross spectra analysis in a 100 m-long transect sampled at 1m apart, on Vertic and Typic Argiudol soils under no tillage [NT] from a commercial farm in San Antonio de Areco, 34 grades 15032.4200 S, 5925019.9300 W, Ondulate pampa region, Argentina. Although spectrum and cospectrum analysis showed several cyclic locations, only sites at approximately 2.6 m, 4mand 9mwere significant [p minor to 0.05]. These distances are clearly related with tractors axles and combine harvester paths, thus suggesting the importance of those operations on soil variables. An autoregressive state space modeling approach was used to integrate the spatial information and to model BD, WC and OC in different transects at 10m and 30m apart. With the spatial relationship between BD and OC we create predictive models that explain 63 per cent of the OC data and 54 per cent of the BD data over a 2740 m-long transect. However, it was not possible to predict WC, despite the spatial correlation observed among the soil variables. The low importance of WC in the modeling process of BD and OC, and the large dominance of the autoregressive part in the final model are pointing out that an important surrogate variable is missing, which could be the key for modeling soil variables at different scale. 
653 0 |a UNCONTROLLED TRAFFIC 
653 0 |a SOIL BULK DENSITY 
653 0 |a SOIL ORGANIC CARBON 
653 0 |a WATER CONTENT 
653 0 |a COSPECTRA ANALYSIS 
700 1 |a Rienzi, Eduardo Abel  |9 6319 
700 1 |9 24656  |a Maggi, Alejandro Esteban 
700 1 |a Scroffa, Marcos  |9 36908 
700 1 |a López, Valeria Carolina  |9 29399 
700 1 |a Cabanella, P.  |9 70226 
773 |t Soil and Tillage Research  |g Vol.159 (2016), p.56-66, tbls., grafs. 
856 |u http://ri.agro.uba.ar/files/intranet/articulo/2016rienzi.pdf  |i En reservorio  |q application/pdf  |x MIGRADOS2018  |f 2016rienzi 
856 |u https://www.elsevier.com/  |x MIGRADOS2018  |z LINK AL EDITOR 
942 0 0 |c ARTICULO 
942 0 0 |c ENLINEA 
976 |a AAG 

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